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| 1 | +// This file is part of OpenCV project. |
| 2 | +// It is subject to the license terms in the LICENSE file found in the top-level directory |
| 3 | +// of this distribution and at http://opencv.org/license.html. |
| 4 | +// |
| 5 | +// Copyright (C) 2021, Dr Seng Cheong Loke ([email protected]) |
| 6 | + |
| 7 | +#ifndef __OPENCV_XIMGPROC_SCANSEGMENT_HPP__ |
| 8 | +#define __OPENCV_XIMGPROC_SCANSEGMENT_HPP__ |
| 9 | + |
| 10 | +#include <opencv2/core.hpp> |
| 11 | + |
| 12 | +namespace cv { namespace ximgproc { |
| 13 | + |
| 14 | +/** @brief Class implementing the F-DBSCAN (Accelerated superpixel image segmentation with a parallelized DBSCAN algorithm) superpixels |
| 15 | +algorithm by Loke SC, et al. @cite loke2021accelerated for original paper. |
| 16 | +
|
| 17 | +The algorithm uses a parallelised DBSCAN cluster search that is resistant to noise, competitive in segmentation quality, and faster than |
| 18 | +existing superpixel segmentation methods. When tested on the Berkeley Segmentation Dataset, the average processing speed is 175 frames/s |
| 19 | +with a Boundary Recall of 0.797 and an Achievable Segmentation Accuracy of 0.944. The computational complexity is quadratic O(n2) and |
| 20 | +more suited to smaller images, but can still process a 2MP colour image faster than the SEEDS algorithm in OpenCV. The output is deterministic |
| 21 | +when the number of processing threads is fixed, and requires the source image to be in Lab colour format. |
| 22 | +*/ |
| 23 | +class CV_EXPORTS_W ScanSegment : public Algorithm |
| 24 | +{ |
| 25 | +public: |
| 26 | + virtual ~ScanSegment(); |
| 27 | + |
| 28 | + /** @brief Returns the actual superpixel segmentation from the last image processed using iterate. |
| 29 | +
|
| 30 | + Returns zero if no image has been processed. |
| 31 | + */ |
| 32 | + CV_WRAP virtual int getNumberOfSuperpixels() = 0; |
| 33 | + |
| 34 | + /** @brief Calculates the superpixel segmentation on a given image with the initialized |
| 35 | + parameters in the ScanSegment object. |
| 36 | +
|
| 37 | + This function can be called again for other images without the need of initializing the algorithm with createScanSegment(). |
| 38 | + This save the computational cost of allocating memory for all the structures of the algorithm. |
| 39 | +
|
| 40 | + @param img Input image. Supported format: CV_8UC3. Image size must match with the initialized |
| 41 | + image size with the function createScanSegment(). It MUST be in Lab color space. |
| 42 | + */ |
| 43 | + CV_WRAP virtual void iterate(InputArray img) = 0; |
| 44 | + |
| 45 | + /** @brief Returns the segmentation labeling of the image. |
| 46 | +
|
| 47 | + Each label represents a superpixel, and each pixel is assigned to one superpixel label. |
| 48 | +
|
| 49 | + @param labels_out Return: A CV_32UC1 integer array containing the labels of the superpixel |
| 50 | + segmentation. The labels are in the range [0, getNumberOfSuperpixels()]. |
| 51 | + */ |
| 52 | + CV_WRAP virtual void getLabels(OutputArray labels_out) = 0; |
| 53 | + |
| 54 | + /** @brief Returns the mask of the superpixel segmentation stored in the ScanSegment object. |
| 55 | +
|
| 56 | + The function return the boundaries of the superpixel segmentation. |
| 57 | +
|
| 58 | + @param image Return: CV_8UC1 image mask where -1 indicates that the pixel is a superpixel border, and 0 otherwise. |
| 59 | + @param thick_line If false, the border is only one pixel wide, otherwise all pixels at the border are masked. |
| 60 | + */ |
| 61 | + CV_WRAP virtual void getLabelContourMask(OutputArray image, bool thick_line = false) = 0; |
| 62 | +}; |
| 63 | + |
| 64 | +/** @brief Initializes a ScanSegment object. |
| 65 | +
|
| 66 | +The function initializes a ScanSegment object for the input image. It stores the parameters of |
| 67 | +the image: image_width and image_height. It also sets the parameters of the F-DBSCAN superpixel |
| 68 | +algorithm, which are: num_superpixels, threads, and merge_small. |
| 69 | +
|
| 70 | +@param image_width Image width. |
| 71 | +@param image_height Image height. |
| 72 | +@param num_superpixels Desired number of superpixels. Note that the actual number may be smaller |
| 73 | +due to restrictions (depending on the image size). Use getNumberOfSuperpixels() to |
| 74 | +get the actual number. |
| 75 | +@param slices Number of processing threads for parallelisation. Setting -1 uses the maximum number |
| 76 | +of threads. In practice, four threads is enough for smaller images and eight threads for larger ones. |
| 77 | +@param merge_small merge small segments to give the desired number of superpixels. Processing is |
| 78 | +much faster without merging, but many small segments will be left in the image. |
| 79 | +*/ |
| 80 | +CV_EXPORTS_W cv::Ptr<ScanSegment> createScanSegment(int image_width, int image_height, int num_superpixels, int slices = 8, bool merge_small = true); |
| 81 | + |
| 82 | +}} // namespace |
| 83 | +#endif |
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